What are the hardware requirements for DeepSeek R1 AWQ?

DeepSeek R1 AWQ requires approximately 225 GB of VRAM and supports a context window of 160K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DeepSeek R1 AWQ and how large is it?

DeepSeek R1 AWQ is developed by cognitivecomputations, a model with 671b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate DeepSeek R1 AWQ?

DeepSeek R1 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

DeepSeek R1 AWQ by cognitivecomputations — VRAM 225GB, 160K context

Name: DeepSeek R1 AWQ
Author: cognitivecomputations

DeepSeek R1 AWQ is an open-source language model by cognitivecomputations. Features: 671b LLM, VRAM: 225GB, Context: 160K, License: mit, Quantized, LLM Explorer Score: 0.18.

4-bit Awq Base model:deepseek-ai/deepsee... Base model:quantized:deepseek-... Conversational Custom code Deepseek v3 En Endpoints compatible Quantized Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/QuixiAI/DeepSeek-R1-AWQ

DeepSeek R1 AWQ Parameters and Internals

LLM Name	DeepSeek R1 AWQ
Repository 🤗	https://huggingface.co/QuixiAI/DeepSeek-R1-AWQ
Base Model(s)	DeepSeek R1 deepseek-ai/DeepSeek-R1
Model Size	671b
Required VRAM	225 GB
Updated	2026-07-28
Maintainer	cognitivecomputations
Model Type	deepseek_v3
Model Files	5.0 GB: 1-of-74 5.0 GB: 2-of-74 5.0 GB: 3-of-74 5.0 GB: 4-of-74 5.0 GB: 5-of-74 5.0 GB: 6-of-74 5.0 GB: 7-of-74 5.0 GB: 8-of-74 5.0 GB: 9-of-74 5.0 GB: 10-of-74 5.0 GB: 11-of-74 5.0 GB: 12-of-74 5.0 GB: 13-of-74 5.0 GB: 14-of-74 5.0 GB: 15-of-74 5.0 GB: 16-of-74 5.0 GB: 17-of-74 5.0 GB: 18-of-74 5.0 GB: 19-of-74 5.0 GB: 20-of-74 5.0 GB: 21-of-74 5.0 GB: 22-of-74 5.0 GB: 23-of-74 5.0 GB: 24-of-74 5.0 GB: 25-of-74 5.0 GB: 26-of-74 5.0 GB: 27-of-74 5.0 GB: 28-of-74 5.0 GB: 29-of-74 5.0 GB: 30-of-74 5.0 GB: 31-of-74 5.0 GB: 32-of-74 5.0 GB: 33-of-74 5.0 GB: 34-of-74 5.0 GB: 35-of-74 5.0 GB: 36-of-74 5.0 GB: 37-of-74 5.0 GB: 38-of-74 5.0 GB: 39-of-74 5.0 GB: 40-of-74 5.0 GB: 41-of-74 5.0 GB: 42-of-74 5.0 GB: 43-of-74 5.0 GB: 44-of-74 5.0 GB: 45-of-74
Supported Languages	en zh
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	DeepseekV3ForCausalLM
License	mit
Context Length	163840
Model Max Length	163840
Transformers Version	4.49.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	129280
Torch Data Type	bfloat16

Rank the DeepSeek R1 AWQ capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to DeepSeek R1 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
DeepSeek V3 AWQ	160K / 351.9 GB	247	36
DeepSeek R1 0528 AWQ	160K / 205 GB	163	19
DeepSeek V3.0324 AWQ	160K / 351.9 GB	16	23
DeepSeek V3.1 Terminus 4bit	160K / 190.1 GB	42	2
DeepSeek V3.1 8bit	160K / 177.8 GB	4268	3
RakutenAI 3.0 MLX 4bit	160K / 198.7 GB	28	2
DeepSeek V3.1 4bit	160K / 190.1 GB	2974	6
DeepSeek V3.1 Base 4bit	160K / 190.1 GB	43	3
DeepSeek R1 0528 5bit	160K / 231 GB	66	3
R1 1776	160K / 243.4 GB	855	2324

Note: green Score (e.g. "73.2") means that the model is better than QuixiAI/DeepSeek-R1-AWQ.